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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.
SBC: Clostra, Inc. Topic: DTRA162001
Deep Learning for standoff detection of Special Nuclear Material (DLeN) applies the same deep learning techniques that allow computers to beat human performance in image recognition and the game of Go to detecting Special Nuclear Material. Spectral analysis and signal processing can in some cases be augmented by the use of much larger neural nets that conduct much deeper analysis of features of th ...SBIR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
SBC: Arete Associates Topic: DTRA162002
Aret Associates and Oak Ridge National Laboratory (ORNL) propose an interdisciplinary effort to further develop and validate a robust, operational biomonitoring application that can process soil microbiome data to reliably detect episodic and low-level chronic contamination while maintaining low false alarm rate.The Phase II SBIR work will build upon the successful Phase I proof-of-concept demonst ...SBIR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
SBC: Physical Optics Corporation Topic: DTRA152006
To address the DTRA need for enhanced island-mode operation and strategies for defense critical infrastructure (DCI) in the event of commercial power grid loss or disruption due to an electromagnetic pulse (EMP) or high-power microwaves (HPMs), Physical Optics Corporation (POC) has developed an Optimizing power Availability and Sustainability in Islanded Sites (OASIS) methodology. This solution is ...SBIR Phase II 2018 Department of DefenseDefense Threat Reduction Agency